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» Injector: Mining Background Knowledge for Data Anonymization
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KDD
2004
ACM
148views Data Mining» more  KDD 2004»
14 years 5 months ago
Interestingness of frequent itemsets using Bayesian networks as background knowledge
The paper presents a method for pruning frequent itemsets based on background knowledge represented by a Bayesian network. The interestingness of an itemset is defined as the abso...
Szymon Jaroszewicz, Dan A. Simovici
DKE
2010
167views more  DKE 2010»
13 years 2 months ago
Discovering private trajectories using background information
Trajectories are spatio-temporal traces of moving objects which contain valuable information to be harvested by spatio-temporal data mining techniques. Applications like city traf...
Emre Kaplan, Thomas Brochmann Pedersen, Erkay Sava...
DATAMINE
2010
133views more  DATAMINE 2010»
13 years 5 months ago
Using background knowledge to rank itemsets
Assessing the quality of discovered results is an important open problem in data mining. Such assessment is particularly vital when mining itemsets, since commonly many of the disc...
Nikolaj Tatti, Michael Mampaey
ICDM
2005
IEEE
157views Data Mining» more  ICDM 2005»
13 years 10 months ago
Blocking Anonymity Threats Raised by Frequent Itemset Mining
In this paper we study when the disclosure of data mining results represents, per se, a threat to the anonymity of the individuals recorded in the analyzed database. The novelty o...
Maurizio Atzori, Francesco Bonchi, Fosca Giannotti...